Identifying changes in China's Bohai and Yellow Sea fisheries resources using a causality-based indicator framework, convergent cross-mapping, and structural equation modeling

Abstract

There is growing evidence that the number of fish stocks that are being harvested at biologically unsustainable levels has increased due to a number of threats. In order to identify the key threats to fisheries resources in the Bohai Sea and Yellow Sea, a causality-based indicator system of fish stock trends and main influencing factors was developed in this study. The causal relationship and influence degree of the driving factors were determined by using the method of convergent cross-mapping, and the structural equation model of fisheries resources change under the influence of multiple factors was established. The results showed that the path coefficients of anthropogenic factors were 1.25 and 1.00 in the Bohai Sea and Yellow Sea, respectively, which were obvious higher than that of environmental factors (0.88 and 0.01), so the influence of anthropogenic factors on fisheries resources was greater than that of environmental factors. There are similarities and differences among the key factors affecting the decline of fisheries resources in the two sea areas. For anthropogenic factors, marine catch and mariculture are the main driving forces in the Bohai Sea and Yellow Sea, followed by the size of marine protected areas. For environmental factors, COD and reactive phosphorus concentration affect the fisheries in the Bohai Sea and Yellow Sea, respectively. Furthermore, some pertinent suggestions were given in this study according to the characteristics of fisheries resources in the Bohai Sea and Yellow Sea. These findings will help fisheries managers in China protect fisheries resources and the marine environment more effectively, and provide a research foundation to support the sustainable development of China's fisheries in the context of resources decline and environmental degradation.

Keywords

• Fisheries resources
• Anthropogenic factors
• Environmental factors
• Structural equation models